Hang Cai
ABSTRACT
Body Sensor Network (BSN) -- a network of body-worn wireless health monitoring sensors -- have a tremendous potential to remove the space and time restrictions on health management. Given the importance of the data BSNs collect for improved health outcomes, securing the data from unauthorized tampering is essential. A compromised (or externally influenced) sensor in a BSN may generate erroneous patient data leading to, among other things, wrong diagnosis and treatment. In this paper, we present a novel approach to address the problem of detecting maliciously induced morphological alterations in the ECG signal (i.e., inducing changes to its shape). Our approach works by correlating the ECG signals with synchronously measured arterial blood pressure (ABP) signal measured using a distinct (and un-compromised) sensor. Initial analysis of our system demonstrates promising results, with 99.75% accuracy in detecting ECG signal morphological alterations for healthy patients with normal sinus rhythms.
- H. Cai and K. K. Venkatasubramanian. Sift: Multi physiological signal feature correlation-based sensor compromise detection in body sensor networks. Technical Report WPI-CS-TR-14-04, Worcester Polytechnic Institute - Computer Sciences Department, July 2014.Google Scholar
- A. L. Goldberger, L. A. N. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-K. Peng, and H. E. Stanley. Physiobank, physiotoolkit, and physionet: Components of a new research resource for complex physiologic signals. Circulation, 101(23): e215--e220, 2000.Google ScholarCross Ref
- O. Malgina, J. Milenkovic, E. Plesnik, M. Zajc, and J. F. Tasic. Ecg signal feature extraction and classification based on r peaks detection in the phase space. In GCC Conference and Exhibition (GCC), 2011 IEEE, pages 381--384. IEEE, 2011.Google ScholarCross Ref
- T. Rocha, S. Paredes, P. de Carvalho, J. Henriques, and M. Antunes. Phase space reconstruction approach for ventricular arrhythmias characterization. In Engineering in Medicine and Biology Society, 2008. 30th Annual International Conference of the IEEE, pages 5470--5473. IEEE, 2008.Google ScholarCross Ref
Index Terms
- Detecting malicious morphological alterations of ECG signals in body sensor networks
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